DocumentCode
240359
Title
The evident use of evidence theory in big data analytics using cloud computing
Author
Mcheick, Hamid ; Mohammad, Atif Farid
Author_Institution
Comput. Sci. Dept., Univ. of Quebec at Chicoutimi, Chicoutimi, QC, Canada
fYear
2014
fDate
4-7 May 2014
Firstpage
1
Lastpage
6
Abstract
We live in the world of evidence. This research survey comprises of several research works and has an example implying dempster-shafer theory of evidence. We have witnessed several advances in computational performance, which have brought us the design and development of high-performance computing simulation tools. It is a fact that we have to account for uncertainty, while generating such high-performance systems using such simulation tools can fail in service performance predictions. We have seen that evidence theory is utilized to measure uncertainty in terms of the uncertain measures of belief and plausibility. It is also witnessed in computing community that Cloud computing has provided a flexible and scalable infrastructures to grow beyond contemporary borders to the organizations as wells the users everyday use of services. It also has increased availability of high-performance computing applications to small/ medium-sized businesses as well as academic users to work with. This paper also sheds light on Cloud computing and Service-Oriented Architecture.
Keywords
Big Data; cloud computing; data analysis; inference mechanisms; service-oriented architecture; uncertainty handling; Big Data analytics; Dempster-Shafer theory; cloud computing; evidence theory; service-oriented architecture; uncertainty measure; Abstracts; Computational modeling; Data models; Forgery; Personnel; Cloud Computing; Evidence Theory; High-Performance Computing; Simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on
Conference_Location
Toronto, ON
ISSN
0840-7789
Print_ISBN
978-1-4799-3099-9
Type
conf
DOI
10.1109/CCECE.2014.6901158
Filename
6901158
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